LLM with flant5 updated

app.py

@@ -1,4 +1,21 @@
 import streamlit as st
+import os
+
+from langchain import PromptTemplate, HuggingFaceHub, LLMChain
 
 x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+st.write(x, 'squared is', x * x)
+
+# https://cobusgreyling.medium.com/langchain-creating-large-language-model-llm-applications-via-huggingface-192423883a74
+# !pip install langchain[all]
+template = """Question: {question}
+
+Answer: Let's think step by step."""
+prompt = PromptTemplate(template=template, input_variables=["question"])
+llm=HuggingFaceHub(repo_id="google/flan-t5-xl", model_kwargs={"temperature":1e-10})
+
+question = "When was Google founded?"
+
+# print(llm.run(question))
+# d=LLMChain(llm=llm,prompt=prompt)
+st.write(LLMChain.run(question))